Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add xuansenpa1/skillrevise --skill economic-dispatchgit clone --depth 1 https://github.com/xuansenpa1/skillreviseWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/xuansenpa1/skillrevise/economic-dispatch)<a href="https://agentmods.dev/skills/xuansenpa1/skillrevise/economic-dispatch"><img src="https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/economic-dispatch/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/xuansenpa1/skillrevise/economic-dispatch"><img src="https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/economic-dispatch.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00037 | $0.01436 |
| Opus 5 | $0.00018 | $0.00718 |
| Sonnet 5 | $0.00007 | $0.00287 |
| Haiku 4.5 | $0.00004 | $0.00144 |
Grade A, and why
economic-dispatch scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to economic-dispatch — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Economic Dispatch
Economic dispatch minimizes total generation cost while meeting load demand and respecting generator limits.
Generator Data Indices
MATPOWER generator array columns (0-indexed):
| Index | Field | Description |
|---|---|---|
| 0 | GEN_BUS | Bus number (1-indexed) |
| 8 | PMAX | Maximum real power (MW) |
| 9 | PMIN | Minimum real power (MW) |
# Use bus number mapping (handles non-contiguous bus numbers)
bus_num_to_idx = {int(buses[i, 0]): i for i in range(n_bus)}
gen_bus = [bus_num_to_idx[int(g[0])] for g in gens]
pmax_MW = gen[8]
pmin_MW = gen[9]
Cost Function Format
MATPOWER gencost array (polynomial type 2):
| Index | Field | Description |
|---|---|---|
| 0 | MODEL | 2 = polynomial |
| 1 | STARTUP | Startup cost ($) |
| 2 | SHUTDOWN | Shutdown cost ($) |
| 3 | NCOST | Number of coefficients |
| 4+ | coeffs | Cost coefficients (highest order first) |
For quadratic (NCOST=3): coefficients are [c2, c1, c0] at indices 4, 5, 6 For linear (NCOST=2): coefficients are [c1, c0] at indices 4, 5
Cost = c₂·P² + c₁·P + c₀ ($/hr) where P is in MW.
Optimization Formulation
import cvxpy as cp
Pg = cp.Variable(n_gen) # Generator outputs in per-unit
# Objective: minimize total cost (handles variable NCOST)
cost = 0
for i in range(n_gen):
ncost = int(gencost[i, 3])
Pg_MW = Pg[i] * baseMVA
if ncost >= 3:
# Quadratic: c2*P^2 + c1*P + c0
c2, c1, c0 = gencost[i, 4], gencost[i, 5], gencost[i, 6]
cost += c2 * cp.square(Pg_MW) + c1 * Pg_MW + c0
elif ncost == 2:
# Linear: c1*P + c0
c1, c0 = gencost[i, 4], gencost[i, 5]
cost += c1 * Pg_MW + c0
else:
# Constant cost
cost += gencost[i, 4] if ncost >= 1 else 0
# Generator limits (convert MW to per-unit)
constraints = []
for i in range(n_gen):
pmin = gens[i, 9] / baseMVA
pmax = gens[i, 8] / baseMVA
constraints.append(Pg[i] >= pmin)
constraints.append(Pg[i] <= pmax)
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 174 lines · 37 tokens per session scan A 907586a8ab5d
economic-dispatch is a skill published in the GitHub repository xuansenpa1/skillrevise (55 stars, last pushed 4d ago), licensed MIT. It adds 37 tokens to every session and 1,436 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to economic-dispatch, differing in 0 lines, and is treated as a copy.
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